Scientific explanations, which include a claim, evidence, and reasoning (CER), are frequently used to measure students' deep conceptual understandings of science. In this study, we developed an automated scoring approach for the CER that students constructed as a part of virtual inquiry (e.g., formulating questions, analyzing data, and warranting claims) in an intelligent tutoring system (ITS), called Inq-ITS. Results showed that the automated scoring of CER was strongly correlated with human scores when validated using independent sets of data from both the same inquiry task/question, as well as when using data from a different inquiry task/question. These findings imply that automated CER is a very promising approach to reliably and efficiently score scientific explanations in open response format for both small- and largescale assessments. It also provides Inq-ITS with the capability to assess the full complement of inquiry practices described by NGSS. [For the full proceedings, see ED596512.]